This repository contains Supporting Material with Python and R code to accompany the following publication and links to download data and supporting materials:

              **"TTILE"**

                                  (link to paper and DOI once published).
                                  
                                  Corresponding author: Leonardo Bertini 
                                  
                                  e-mail :  l.bertini@nhm.ac.uk  | l.bertini@bristol.ac.uk

                The code is distributed under the MIT license https://en.wikipedia.org/wiki/MIT_License

This project was supported by:

• 4D-Reef, a Marie Skłodowska-Curie Innovative Training Network funded by European Union Horizon 2020 research and innovation programme
• The Natural History Museum Science Investment Fund.
• SYNTHESIS+ museum initiative transnational access.

This work was a joint effort across people from the following institutions:

Below, you'll find a brief description of directories in this repository, which might have their own 'README' files with further info.

Data

• Contains download links to remote sensing data extracted for datapoints representing locations where there are available literature as well as metadata for museum specimens.

Python Code

• Remote sensing extraction of SST, Light Availability and Turbidity spatially gridded data from remote sensing products.
• Code used for processing literature review data based (source table imported by the code in Data)

R Code

• Code for statistical analyses and figures.